Please provide lectures for intermediate level and above as well.


n71117314067

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems,
If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)


dooleyz3525

인프런 10주년! 사랑주간 전체 할인

Deep Learning CNN Complete Guide - Pytorch Version

Thank you for the positive feedback. We are planning to prepare intermediate and advanced level courses in the future.


PyTorch

pytorch

Deep Learning(DL)

딥러닝

딥러닝실전프로젝트

컴퓨터비전

입문

초급

중급이상

파이토치

Computer Vision(CV)

합성곱신경망

Course Introduction


An Overview of Deep Learning and Handling Tensors


Deep Learning Based Understanding - Gradient Descent


Deep Learning Based Understanding - Backpropagation and Activation Functions


Pytorch Framework - 01


Pytorch Framework - 02


Pytorch Framework - 03


Understanding CNNs


Weight Initialization, Batch Normalization, Drop Out, Learning Rate Scheduler, and Weight Decay


Dataset and DataLoader


Utilizing Pretrained Models and Fine-Tuning Training


Modularize ModelCheckpoint, EarlyStopping, and Trainer classes and use torchmetrics.


Image Data Augmentation


Advanced Image Data Augmentation - CutMix


Understanding CNN Models - AlexNet, VGG, GoogLeNet


Understanding CNN Models - ResNet Details and EfficientNet Overview


Comprehensive Practice 1 - Optimizing a Dog Breed Identification Model for 120 Breeds


Comprehensive Practice 2 - Kaggle Plant Pathology (Tree Leaf Disease Diagnosis) Competition


In conclusion,
